Intelligent Sliding Mode Control for Quadrotor Trajectory Tracking Under External Disturbances
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Abstract
This paper proposes particle swarm optimization (PSO) and cuckoo search (CS) approaches based on the sliding mode controller (SMC) structure for the unmanned quadrotor’s flights. The control law is derived from the Lyapunov theory to guarantee the closed-loop stability. Despite unknown disturbance bounds, the simulation experiments on the nonlinear quadrotor’s model prove that these intelligent controllers are very effective for position control, attitude stabilization, automatic take-off and landing, and trajectory tracking missions. Conducted comparisons to the intelligent proportional integral derivative structure through PSO, CS, genetic algorithms, neural networks, fuzzy logic, and some hybrid techniques proposed in previous works of quadrotor control, confirm the superiority of PSO-SMC in terms of robustness and adaptability.
Cite this article as: N. El Gmili, K. El Hamidi, M. Mjahed, A. El Kari and H. Ayad, “Intelligent sliding mode control for quadrotor trajectory tracking under external disturbances,” Electrica, 24(2), 304-317, 2024.